Yet there’s considerable differentiation between these co-ops in terms of the business models that support them. AdRoll’s IntentMap, for example, comes with no tiered payment or subscription charges, as MediaMath’s Helix does.

AdRoll doesn’t plan to monetize the B2B data co-op directly, it just wants to expand the budget pool for its existing ad-serving business. “Once you introduce the opportunity for people to buy their way in, you change the value prop and create weird incentives,” said Berke.

For instance, if AdRoll collected revenue on its IntentMap, would it share that back with the clients who opt in their first-party data? And if so, how?

Krux solves the problem by embracing an open market, where participating companies can browse or sell their own data to others.

MediaMath monetizes the volume of data a client uses or charges a subscription.

While AdRoll’s leadership discussed the pros and cons of selling access to the pooled data, Berke said when brands buy data and services at an extra cost, it inflates the media portion of the campaign budget.

The different models also reflect different client rosters. MediaMath’s co-op consists of about 300 companies, but is more focused on enterprise clients. AdRoll has 3,000 participants, mostly SMBs, who want to improve their targeting for free, even if it means exposing their own data to a shared pool.

Although Berke noted that with 3,000 participants, none of which represent meaningful segments of the data, there aren’t concerns over competitive conquesting or special first-party data accommodations.

DataDog is a cloud monitoring service that has participated in the AdRoll IntentMap for the past few months. “We were skeptical,” said the company’s demand-generation manager, Rob DiNuzzo. “Most of our target market – very technical mid-manager, directors, system admins – have ad blockers on, and they don’t surf around and click on things.”

With AdRoll’s B2B lead-gen, DiNuzzo said the volume of inventory and leads was consistently higher than campaigns on any platform beside Google. So much so that when the company bumped up the campaign from test budgets in January, DataDog “watched it like a hawk” to make sure the leads were legitimate.

“The success on the back end is there as well,” he said. “A lot of people are converting into sales opps and sales wins.”

“We wanted to keep the value as simple as possible,” said Berke. “if you can deliver more audiences and a better data set for no cost, that’s a powerful proposition.”